3 March 2017 Intraoperative 3D ultrasound guidance system for permanent breast seed implantation
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Abstract
Permanent breast seed implantation (PBSI) is a single-visit technique for accelerated partial breast irradiation that uses a template and needles to implant seeds of Pd-103 under 2D ultrasound (US) guidance. The short treatment time is advantageous given the widely hypothesized link between treatment burden and mastectomy use. However, limitations of 2D US contribute to high operator dependence and seed placement error that we aim to address by developing a 3D US guidance system. A 3D US scanner for PBSI and a mechanism for template localization have been developed and validated. The 3D US system mechatronically moves and tracks a 2D US transducer over a 5 cm translation and 60° tilt, reconstructing the 2D images into a 3D volume as they are acquired. Additionally, a localizing arm, tracked via encoded joints and mounted to the scanner, determines template position by localizing divots on a modified needle template. Volume reconstruction was validated using linear measurements of a grid phantom and volumetric measurements of two surgical cavity phantoms. Localizing arm measurement accuracy was established using a testing jig with divots at known positions. Imaging volume was rigidly registered to scanner geometry using a string phantom mounted to a test jig. Lastly, volunteer scans were conducted to demonstrate clinical applicability. Median linear and average volumetric measurements were within ±1.4% of nominal and ±4.1% of water displacement measurements, respectively. Median measurement accuracy of the localizing arm was 0.475 mm. Imaging volume target registration error was 0.458 mm. Volunteer scans produced clinical quality images.
Conference Presentation
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Justin Michael, Daniel Morton, Deidre Batchelar, Michelle Hilts, Aaron Fenster, "Intraoperative 3D ultrasound guidance system for permanent breast seed implantation", Proc. SPIE 10135, Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling, 101351B (3 March 2017); doi: 10.1117/12.2254461; https://doi.org/10.1117/12.2254461
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